GPU-as-a-Service on KubeFlow: Fast, Scalable and Efficient ML

Machine Learning (ML) and Deep Learning (DL) involve compute and data intensive tasks. In order to maximize our model accuracy, we want to train on larger datasets, evaluate a variety of algorithms, and try out different parameters for each algorithm (hyper-parameter tuning). As our datasets and model complexity grow, so does the time we need to wait for our jobs to complete, leading to inefficient use of our time. We end up running fewer iterations and tests or working on smaller datasets as a result. NVIDIA GPUs are a great tool to accelerate our data science work.